有Edgeworth展式的分布的随机加权逼近的重对数律

本文研究了未知分布的逼近问题，利用随机加权法，给出了有Edgeworth展式的一类（未知）分布的模拟分布，证明了在一定条件下，模拟分布与未知分布的逼近精度达到O(n^-1√lnlnn），称之为随机加权逼近的重对数律。     

用随机模糊方法研究合理确定工程项目工期

站在兼顾业主与建造商的公正立场,基于网络优化技术基础上并以系统的观点,采用随机模糊数学方法研究合理确定项目工期,进而用实际项目进行分析验证,是一种科学合理确定工期的方法.     

响应变量随机缺失下的半参变系数模型的均值估计

在响应变量随机缺失时,研究了半参数变系数模型响应变量均值的借补估计.首先利用完整个体估计模型中的参数与非参数部分,然后再用借补方法与加权借补方法估计响应变量的均值.最后求出了估计的渐近偏差与渐近方差,研究了所得到的估计的渐近性质,并进行模拟比较.     

Nonlinear Time Series Analysis Since 1990:Some Personal Reflections

Abstract I reflect upon the development of nonlinear time series analysis since 1990 by focusing on five majorareas of development. These areas include the interface between nonlinear time series analysis and chaos,thenonparametric/semiparametric approach,nonlinear state space modelling,financial time series and nonlinearmodelling of panels of time series.     

带有无限到达源的Re-entrant Line的稳定性

用Foster判别准则,Weiss[13]给出了带有无限到达源的两站三步re-entrant line的稳定性的充分条件．本文用两种不同的方法得到了其稳定性的充分必要条件,即: 二维随机游动方法和Foster判别准则．同时,我们又用流体模型方法得到了系统稳定的充分条件,大大地简化了Weiss[13]的证明．     

Concentration for self‐bounding functions and an inequality of Talagrand

We see that the entropy method yields strong concentration results for general self‐bounding functions of independent random variables. These give an improvement of a concentration result of Talagrand much used in discrete mathematics. © 2006 Wiley Periodicals, Inc. Random Struct. Alg., 2006     

外加电场下激光诱导Al等离子体特性的实验研究

由Q-Nd:YAG脉冲激光(波长1.06μm,脉宽10 ns)烧蚀Al靶产生等离子体.观测了在低气压和直流电场条件下的Al等离子体发射光谱.研究了激光功率密度和直流电场对各谱线强度的影响,分析了谱线半高全宽与外加电压,等离子体电子温度与激光能量的变化规律.结果表明,直流电场对铝原子谱线强度有显著的增强,铝原子谱线的半高全宽与直流电场的外加电压基本上呈线性关系.     

随机动力系统的进展和问题

本文主要介绍随机动力系统的主要成果和进一步研究的问题。     

Moderate and Small Deviations for the Ranges of One-Dimensional Random Walks

We establish moderate and small deviations for the ranges of integer valued random walks. Our theorems apply to the limsup and the liminf laws of the iterated logarithm. We establish moderate and small deviations for the ranges of integer valued random walks. Our theorems apply to the limsup and the liminf laws of the iterated logarithm.     

Learning Markov chains in fractal compression of image data

In a recent paper [17] we proposed a stochastic algorithm which generates optimal probabilities for the decompression of an image represented by the fixed point of an IFS system (SAOP). We show here that such an algorithm is in fact a non trivial example of Generalized Random System with Complete Connections. We also exhibit a generalization which could represent the solution to the inverse problem for an image with grey levels, if a fixed set of contraction maps is available. Received: 1 July 2002